Triple
T1103783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Grande do Norte |
E25441
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Nova Cruz
Nova Cruz is a municipality in the Brazilian state of Rio Grande do Norte, known as a regional commercial and service center in the Agreste Potiguar area.
|
E127487
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nova Cruz | Statement: [Rio Grande do Norte, hasCity, Nova Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nova Cruz Context triple: [Rio Grande do Norte, hasCity, Nova Cruz]
-
A.
Guilherme
Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
-
B.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
-
C.
Santos
Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
-
D.
Santos
Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
-
E.
Darlan
Darlan is a French surname most notably associated with François Darlan, a prominent admiral and political figure in Vichy France during World War II.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nova Cruz Triple: [Rio Grande do Norte, hasCity, Nova Cruz]
Generated description
Nova Cruz is a municipality in the Brazilian state of Rio Grande do Norte, known as a regional commercial and service center in the Agreste Potiguar area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nova Cruz Target entity description: Nova Cruz is a municipality in the Brazilian state of Rio Grande do Norte, known as a regional commercial and service center in the Agreste Potiguar area.
-
A.
Guilherme
Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
-
B.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
-
C.
Santos
Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
-
D.
Santos
Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
-
E.
Darlan
Darlan is a French surname most notably associated with François Darlan, a prominent admiral and political figure in Vichy France during World War II.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5391a4a88190b7ef6993b2b85b08 |
completed | March 7, 2026, 4:34 p.m. |
| NEDg | Description generation | batch_69ac542bac488190b7d6c2ed9a919779 |
completed | March 7, 2026, 4:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac54971fc88190b009a05180f10cf5 |
completed | March 7, 2026, 4:38 p.m. |
Created at: March 1, 2026, 7:43 p.m.